Multiplexed embryo profiling links cellular state to zygotic genome activation in single cells.
7 affiliations
- 1Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
- 2Systems Biology PhD program, Life Science Zurich Graduate School, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
- 3Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
- 4The BioVisionCenter, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
- 5Molecular Life Sciences PhD program, Life Science Zurich Graduate School, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
- 6Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland. [email protected].
- 7Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland. [email protected].
Abstract
Multicellular self-organization depends on interactions across multiple length scales, yet mapping protein states at high spatial resolution in whole-mount embryos remains challenging. Here, we introduce high-throughput 3D in toto iterative immunofluorescence imaging (3D-4i) and a dedicated computer vision pipeline to quantify morphological and molecular features from subcellular to whole-embryo scales across hundreds of samples. Applying this pipeline to early zebrafish embryos undergoing mid-blastula transition, we determine the cell cycle phase for each cell across the embryo, and uncover the spatiotemporal dynamics by which global meta-synchronous mitotic waves transition to cell cycle desynchronization. Using statistical analysis, we find that the cell cycle phase is the major source of variability in transcription within a division cycle, and combining this with the analysis of key transcription factors and chromatin modifier state, included in our multiplexed dataset, enables accurate prediction of transcriptional output during zygotic genome activation in individual cells. Together, these findings establish 3D-4i as a powerful approach for quantifying multimodal, multiscale biological processes underlying multicellular self-organization.
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BibTeX
@article{hess2026multiplexed,
title = {{Multiplexed embryo profiling links cellular state to zygotic genome activation in single cells.}},
author = {Max Hess and Marvin F Wyss and Edlyn Wu and Gian-Marco Schaniel and Joel Lüthi and Chiara Rebagliati and Daniel Hannuschke and Nadine L Vastenhouw and Darren Gilmour and Shayan Shamipour and Lucas Pelkmans},
journal = {Nature communications},
year = {2026},
month = sep,
doi = {10.1038/s41467-026-77784-7},
url = {https://europepmc.org/article/MED/42897187},
note = {CC BY},
}
RIS
TY - JOUR
TI - Multiplexed embryo profiling links cellular state to zygotic genome activation in single cells.
AU - Max Hess
AU - Marvin F Wyss
AU - Edlyn Wu
AU - Gian-Marco Schaniel
AU - Joel Lüthi
AU - Chiara Rebagliati
AU - Daniel Hannuschke
AU - Nadine L Vastenhouw
AU - Darren Gilmour
AU - Shayan Shamipour
AU - Lucas Pelkmans
PY - 2026
DA - 2026/09/17
JO - Nature communications
DO - 10.1038/s41467-026-77784-7
UR - https://europepmc.org/article/MED/42897187
AB - Multicellular self-organization depends on interactions across multiple length scales, yet mapping protein states at high spatial resolution in whole-mount embryos remains challenging. Here, we introduce high-throughput 3D in toto iterative immunofluorescence imaging (3D-4i) and a dedicated computer vision pipeline to quantify morphological and molecular features from subcellular to whole-embryo scales across hundreds of samples. Applying this pipeline to early zebrafish embryos undergoing mid-blastula transition, we determine the cell cycle phase for each cell across the embryo, and uncover the spatiotemporal dynamics by which global meta-synchronous mitotic waves transition to cell cycle desynchronization. Using statistical analysis, we find that the cell cycle phase is the major source of variability in transcription within a division cycle, and combining this with the analysis of key transcription factors and chromatin modifier state, included in our multiplexed dataset, enables accurate prediction of transcriptional output during zygotic genome activation in individual cells. Together, these findings establish 3D-4i as a powerful approach for quantifying multimodal, multiscale biological processes underlying multicellular self-organization.
SN - 2041-1723
ER -